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黄金科学技术 ›› 2022, Vol. 30 ›› Issue (1): 46-53.doi: 10.11872/j.issn.1005-2518.2022.01.102

• 采选技术与矿山管理 • 上一篇    下一篇

基于NSGA-Ⅱ算法的废石及尾砂混合充填料配比优化

高峰1(),艾浩泉1(),梁耀东2,罗增武2,熊信1,周科平1,杨根1   

  1. 1.中南大学资源与安全工程学院,湖南 长沙 410083
    2.广西高峰矿业有限责任公司,广西 南丹 547205
  • 收稿日期:2021-07-29 修回日期:2021-09-27 出版日期:2022-02-28 发布日期:2022-04-25
  • 通讯作者: 艾浩泉 E-mail:csugaofeng@csu.edu.cn;2269840005@qq.com
  • 作者简介:高峰(1981-),男,湖南怀化人,博士,副教授,从事矿山开采、灾害机理与防治方面的研究工作。csugaofeng@csu.edu.cn
  • 基金资助:
    国家重点研发计划项目“面向固废源头减量的硼镁铁矿精准连续化开采技术与示范”(2020YFC1909801);湖南省自然科学基金项目“寒区冻结裂隙岩体爆破损伤断裂特征与机理研究”(2020JJ4704)

Optimization of Proportioning of Waste Rock and Tailings Mixed Filling Materials Based on NSGA-II Algorithm

Feng GAO1(),Haoquan AI1(),Yaodong LIANG2,Zengwu LUO2,Xin XIONG1,Keping ZHOU1,Gen YANG1   

  1. 1.School of Resources and Safety Engineering, Central South University, Changsha 410083, Hunan, China
    2.Guangxi Gaofeng Mining Co. , Ltd. , Nandan 547205, Guangxi, China
  • Received:2021-07-29 Revised:2021-09-27 Online:2022-02-28 Published:2022-04-25
  • Contact: Haoquan AI E-mail:csugaofeng@csu.edu.cn;2269840005@qq.com

摘要:

为了提高高峰矿尾砂充填体强度和解决井下废石利用问题,开展高峰矿废石及尾砂混合充填材料的最优配比研究,设计了四因素四水平的正交试验,采用极差分析获得了影响充填体强度、料浆泌水率和料浆坍落度的主次因素,得到初步满足矿山要求的配比:料浆浓度为83%,灰砂比为0.25,废尾比为1.5,泵送剂添加量为0.5%。根据正交试验数据建立了28 d充填体强度、料浆泌水率和坍落度的二次多项式回归模型,基于NSGA-Ⅱ算法进行多目标优化,获得最优充填料浆配比。研究结果表明:灰砂比对充填体强度影响最大,料浆浓度和废尾比次之,泵送剂影响最小;灰砂比对料浆泌水率有明显的控制作用,废尾比和料浆浓度次之,泵送剂作用最小;料浆浓度对坍落度影响最大,泵送剂和灰砂比影响次之,废尾比影响最小;多目标优化后的配比:料浆浓度为82.989%,灰砂比为0.240,废尾比为1.419,泵送剂添加量为0.537%,优化后的配比方案所需充填材料成本相比正交试验确定的方案成本下降了2.9%。

关键词: 正交试验, 混合充填材料, 回归模型, 多目标优化, NGSA-Ⅱ算法, gamultiobj函数

Abstract:

With the increasing attention on the environmental protection of resource development and the strict requirements for the discharge of waste rocks,tailings,waste residues and other wastes generated in resource development,it is particularly important to dispose these wastes.The mixed filling of waste rocks and tailings is the most effective way to solve the discharge of mine waste.Taking the underground filling of Gaofeng mine as an example,It is necessary to determine the optimal ratio of waste rock and tailings mixed filling materials.The particle size of tailings and waste rock were analyzed by laser method and sieve method.The chemical composition of waste rock and tailings was obtained by X-ray spectrometry.The orthogonal experiment with four factors and four levels was designed,and the range analysis of the experimental data was carried out.The primary and secondary factors affecting the strength of filling body,slurry bleeding rate and slurry slump were explored,and the filling material ratio that preliminarily met the requirements of the mine was obtained.The slurry concentration is 83%,the ash sand ratio is 0.25,the waste tail ratio is 1.5 and the amount of pumping agent is 0.5%.According to the experimental data,the quadratic polynomial regression model of 28 d filling body strength,slurry bleeding rate and slump was established.The theoretical value and experimental value of the regression model were compared and analyzed.It is found that the relative error is within a reasonable range,indicating that the model has certain reliability for the prediction of filling body performance.Multi-objective optimization Pareto solution set obtained based on NSGA-II algorithm.The mixture ratio of waste rock and tailings filling slurry with good performance and lowest cost was determined.The results are as follows:According to range analysis,The ratio of ash to sand has the greatest influence on the strength of filling body,and the influence of slurry concentration,waste tail ratio and pumping agent decreases in turn.The ash sand ratio has obvious control effect on the slurry bleeding rate,and the waste tail ratio,slurry concentration and pumping agent effect decrease in turn.The slurry concentration has the greatest influence on slump,and the influence of pumping agent,ash sand ratio and waste tail ratio decreases in turn.Without increasing the cost of additional materials,the proportion of waste rock can be appropriately increased to improve the strength of the filling body.The cost of filling material for the optimized scheme is reduced by 2.9% compared with the preliminary scheme determined by orthogonal test,the optimized filling ratio is slurry concentration 82.989%,ash sand ratio 0.240,waste tail ratio 1.419 and pumping agent 0.537%.

Key words: orthogonal test, mixed filling materials, regression model, multi-objective optimization, NGSA-Ⅱ algorithm, gamultiobj function

中图分类号: 

  • TD853

表1

废石和尾砂物理性质"

材料种类真密度/(g·cm-3松散密度/(g·cm-3紧密密度/(g·cm-3孔隙率/%堆积密实度
废石2.7221.5971.93429.470.709
尾砂3.0911.3131.76043.060.569

图1

尾砂粒径分布图"

图2

废石粒径分布图"

表2

正交试验因素水平"

水平因素
A(料浆浓度)B(灰砂比)C(废尾比)D(泵送剂)
177%1∶43∶70%
279%1∶54∶60.5%
381%1∶65∶51.0%
483%1∶76∶42.0%

表3

正交试验结果"

试验编号因素指标
料浆 浓度/%灰砂比废尾比

泵送剂

/%

28 d抗压 强度/MPa泌水率/%坍落度/cm
1771∶43∶703.17612.8727.8
2771∶54∶60.52.57012.8428.6
3771∶65∶51.02.49811.5927.2
4771∶76∶42.01.69817.6828.7
5791∶44∶61.05.40810.4528.8
6791∶53∶72.03.0199.8629.8
7791∶66∶402.91217.2928.4
8791∶75∶50.52.23312.4329.3
9811∶45∶52.05.33710.3428.8
10811∶56∶41.03.76112.9627.6
11811∶63∶70.53.02213.5328.0
12811∶74∶601.94313.0226.8
13831∶46∶40.57.6227.07026.0
14831∶55∶504.9909.7225.5
15831∶64∶62.03.07314.5526.6
16831∶73∶71.02.74714.2922.3

表4

极差分析结果"

指标因素ABCD因素主次
28 d抗压 强度/MPak12.4865.3862.9913.255B>A>C>D
k23.3933.5853.2493.862
k33.5162.8763.7653.604
k44.6082.1553.9983.282
R2.1223.2311.0070.607
泌水率/%k113.7510.1812.6413.23B>C>A>D
k212.5111.3512.7211.47
k312.4614.2411.0212.32
k411.4114.3613.7513.11
R2.344.182.731.76
坍落度/cmk128.128.727.027.1A>D>B>C
k229.127.927.728.9
k327.827.627.726.5
k425.126.827.628.5
R4.11.80.702.20

图3

不同指标的敏感性因素分析图"

图4

不同灰砂比下的充填体SEM图"

图5

模型预测值与试验值相对误差绝对值"

图6

多目标算法步骤图"

图7

Pareto前沿图"

表5

部分Pareto最优解集"

组号料浆浓度/%灰砂比废尾比泵送剂/%28 d抗压强度/MPa泌水率/%坍落度/cm
182.9880.2481.3711.0877.1856.51726.72
282.9880.2501.1300.8077.8886.51227.35
382.9910.2461.3070.6457.5086.65326.66
482.9900.2501.0721.0447.8246.46827.50
582.9930.2481.2980.7377.5756.52326.75
682.9890.2401.4190.5377.0666.89726.16
782.9900.2421.4120.4997.2136.89126.19
882.9990.2451.4120.4587.3656.89626.21
982.9950.2471.2210.5247.6516.84526.89
1082.9900.2501.1870.9947.6946.36727.26

表6

不同组号的材料成本预算"

组号成本/(元/吨)组号成本/(元/吨)
1129.376120.38
2127.667120.80
3124.068121.58
4130.299123.34
5125.8410128.31
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